Exploring the Difficulties African-American Middle School Girls Face Enacting Computational Algorithmic Thinking over three Years while Designing Games for Social Change

Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that the solution solves the problem, and evaluating the solution based on some set of criteria. CAT is an important scaffolded on-ramp as students develop more advanced computational thinking capabilities and apply computational thinking to solve problems that are more constrained and require greater expertise. Supporting Computational Algorithmic Thinking (SCAT) is both a longitudinal between-subjects research project and a free enrichment program supporting and guiding African-American middle school girls over three years as they iteratively design a set of complex games for social change. This article explores Scholars’ reflections about the difficulties they faced while using CAT capabilities as they engaged in collaborative game design for social change over those three years. We particularly focus on how these difficulties changed over the course of three years as well as new difficulties that emerged from year to year as Scholars become more expert game designers and computational algorithmic thinkers.     

Perception of products by progressive multisensory integration. A study on hammers

The aim of this work is to determine the influence of multisensory (visual-haptic) integration and the level of interaction (seeing photographs, seeing the actual product, touching it and using it) on the perception of products, including perceived ergonomics. The product selected for the experiment was the hammer, as this will help to establish whether emotional design studies can also apply to ‘commercial’ products. Subjective opinions of users were evaluated through semantic differential tests. A factor analysis identified six semantic factors or axes (Quality/Robustness, Ergonomics/Appearance, Innovation, Lightness, Dynamic Effects, and Efficacy). Results show that Lightness and Dynamic Effects are quite sensitive to the level of interaction, while Ergonomics/Appearance is partially affected. However, the perceptions of Innovation, Quality/Robustness and Efficacy are not so affected and they could be detected through a lower level of interaction (i.e. seeing photographs). This suggests that commercial products seem sensitive to emotional design studies and that multisensory integration enhances the perception of the factors that are clearly linked with physical interaction between users and tools, i.e. Ergonomics/Appearance, Lightness and Dynamic Effects. Additionally, it should be highlighted that some aspects related with the ergonomics and ease of use of products are also perceived at different stages of interaction.     

Ontology-Based Network Management: Study Cases and Lessons Learned

Ontology based network management has recently evolved from a theoretical proposal to a more mature technology. As such, it is now being applied in many research projects in a number of different network management and security scenarios. This application has enabled the validation of the main ideas of the proposals and to learn some of the problems that it brings. This paper describes several research projects where ontology based network management proposals were applied, detailing the most important facets of the initial proposals that were used and explaining the main advantages and drawbacks that were found after prototyping these proposals.

Receiver-side semantic reasoning for digital TV personalization in the absence of return channels

Experience has proved that interactive applications delivered through Digital TV must provide personalized information to the viewers in order to be perceived as a valuable service. Due to the limited computational power of DTV receivers (either domestic set-top boxes or mobile devices), most of the existing systems have opted to place the personalization engines in dedicated servers, assuming that a return channel is always available for bidirectional communication. However, in a domain where most of the information is transmitted through broadcast, there are still many cases of intermittent, sporadic or null access to a return channel. In such situations, it is impossible for the servers to learn who is watching TV at the moment, and so the personalization features become unavailable. To solve this problem without sacrificing much personalization quality, this paper introduces solutions to run a downsized semantic reasoning process in the DTV receivers, supported by a pre-selection of material driven by audience stereotypes in the head-end. Evaluation results are presented to prove the feasibility of this approach, and also to assess the quality it achieves in comparison with previous ones.

Universal access in e-voting for the blind

Since the inception of elections and election technologies, all segments of the voting population have never been granted equal access, privacy and security to voting. Modern electronic voting systems have made attempts to include disabled voters but have fallen short. Using recent developments in technology a secure, user centered, multimodal electronic voting system has been developed to study a multimodal approach for providing equity in access, privacy and security in electronic voting. This article will report findings from a study at the Alabama Institute for the Deaf and Blind where more than thirty-five blind or visually impaired participants used the multimodal voting system. The findings suggest that the proposed multimodal approach to voting is easy to use and trustworthy.     

Exploiting synergies between semantic reasoning and personalization strategies in intelligent recommender systems: A case study

Current recommender systems attempt to identify appealing items for a user by applying syntactic matching techniques, which suffer from significant limitations that reduce the quality of the offered suggestions. To overcome this drawback, we have developed a domain-independent personalization strategy that borrows reasoning techniques from the Semantic Web, elaborating recommendations based on the semantic relationships inferred between the user’s preferences and the available items. Our reasoning-based approach improves the quality of the suggestions offered by the current personalization approaches, and greatly reduces their most severe limitations. To validate these claims, we have carried out a case study in the Digital TV field, in which our strategy selects TV programs interesting for the viewers from among the myriad of contents available in the digital streams. Our experimental evaluation compares the traditional approaches with our proposal in terms of both the number of TV programs suggested, and the users’ perception of the recommendations. Finally, we discuss concerns related to computational feasibility and scalability of our approach.     

Parallel approach to NNMF on multicore architecture

We tackle the parallelization of Non-Negative Matrix Factorization (NNMF), using the Alternating Least Squares and Lee and Seung algorithms, motivated by its use in audio source separation. For the first algorithm, a very suitable technique is the use of active set algorithms for solving several non-negative inequality constraints least squares problems. We have addressed the NNMF for dense matrix on multicore architectures, by organizing these optimization problems for independent columns. Although in the sequential case, the method is not as efficient as the block pivoting variant used by other authors, they are very effective in the parallel case, producing satisfactory results for the type of applications where is to be used. For the Lee and Seung method, we propose a reorganization of the algorithm steps that increases the convergence speed and a parallelization of the solution. The article also includes a theoretical and experimental study of the performance obtained with similar matrices to that which arise in applications that have motivated this work.     

Desaturase activities in rat model of insulin resistance induced by a sucrose-rich diet

A sucrose-rich diet, as compared with a similar starch diet, induces a time-dependent typical noninsulin-dependent diabetes syndrome characterized by insulin resistance in rats. Within the first 3 wk, there was glucose intolerance associated with hyperinsulinemia, hypertriglyceridemia, and high plasma FFA. In this study, we examined the effect of the sucrose-rich diet vs. the starch diet during short-(3 wk) and long-term treatment (6 mon) on hepatic Δ9, Δ6, and Δ5 desaturases. These enzymes modulate monounsaturated FA and PUFA biosynthesis, respectively. Sucrose feeding (3 wk) caused an initial hyperinsulinemia that was normalized within 6 mon. In the early period (3 wk), stearoyl-CoA desaturase-1 (SCD-1) mRNA and activity were decreased, whereas Δ6 desaturase mRNA abundance and Δ6 and Δ5 desaturase activities remained unchanged. After 6 mon of sucrose feeding, activities of the Δ9, Δ6, and Δ5 desaturases were each increased. The SCD-1 and Δ6 desaturase mRNA were also correspondingly higher. These increases were consistent with an increase in oleic acid, the 20∶4/18∶2 ratio, and 22∶4n−6 and 22∶5n−6 acids in liver and muscle lipids. On the other hand, the percentage of 22∶6n−3 acid was decreased. In conclusion, a sucrose-rich diet after 6 mon induces an increase in rat liver SCD-1 and Δ6 desaturase mRNA and enzymatic activities that are opposite to the changes reported in insulin-dependent diabetes mellitus. It appears that neither blood insulin levels nor insulin resistance is a factor affecting the Δ9, Δ6, and Δ5 desaturase changes in mRNA and activity found with the sucrose-rich diet.     

The influence of sodium tripolyphosphate and zeolites on detergency of linear alkylbenzene sulfonate in the presence of Mg++

The influence of sodium tripolyphosphate (STPP) and zeolites on the detergency performance of linear alkylbenzene sulfonate (LAS) has been evaluated at different water magnesium ion levels. This study demonstrates that LAS/STPP gives better results in the presence of calcium than in the presence of magnesium, whereas the LAS/zeolite mixture gives better results in the presence of magnesium than in the presence of calcium.